Evidence map›Paper›PMID 33477827›Full record

ArticleInternational journal of molecular sciences2021

Analyzing Low-Level mtDNA Heteroplasmy-Pitfalls and Challenges from Bench to Benchmarking.

Federica Fazzini, Liane Fendt, Sebastian Schönherr, Lukas Forer, Bernd Schöpf, Gertraud Streiter, Jamie Lee Losso, Anita Kloss-Brandstätter, Florian Kronenberg, Hansi Weissensteiner

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Federica FazziniDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, A-6020 Innsbruck, Austria.
Liane FendtDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, A-6020 Innsbruck, Austria.
Sebastian SchönherrDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, A-6020 Innsbruck, Austria.
Lukas ForerDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, A-6020 Innsbruck, Austria.ORCID 0000-0003-2139-7329
Bernd SchöpfDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, A-6020 Innsbruck, Austria.ORCID 0000-0003-0485-1462
Gertraud StreiterDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, A-6020 Innsbruck, Austria.ORCID 0000-0002-4810-2984
Jamie Lee LossoDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, A-6020 Innsbruck, Austria.
Anita Kloss-BrandstätterDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, A-6020 Innsbruck, Austria.ORCID 0000-0002-0873-6704
Florian KronenbergDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, A-6020 Innsbruck, Austria.ORCID 0000-0003-2229-1120
Hansi WeissensteinerDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, A-6020 Innsbruck, Austria.ORCID 0000-0002-2871-8669

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Massive parallel sequencing technologies are promising a highly sensitive detection of low-level mutations, especially in mitochondrial DNA (mtDNA) studies. However, processes from DNA extraction and library construction to bioinformatic analysis include several varying tasks. Further, there is no validated recommendation for the comprehensive procedure. In this study, we examined potential pitfalls on the sequencing results based on two-person mtDNA mixtures. Therefore, we compared three DNA polymerases, six different variant callers in five mixtures between 50% and 0.5% variant allele frequencies generated with two different amplification protocols. In total, 48 samples were sequenced on Illumina MiSeq. Low-level variant calling at the 1% variant level and below was performed by comparing trimming and PCR duplicate removal as well as six different variant callers. The results indicate that sensitivity, specificity, and precision highly depend on the investigated polymerase but also vary based on the analysis tools. Our data highlight the advantage of prior standardization and validation of the individual laboratory setup with a DNA mixture model. Finally, we provide an artificial heteroplasmy benchmark dataset that can help improve somatic variant callers or pipelines, which may be of great interest for research related to cancer and aging.

Indexed as

AgingBenchmarkingDNA-Directed DNA PolymeraseDNA, MitochondrialGenetic Predisposition to DiseaseGenetic VariationGenome, MitochondrialHeteroplasmyHigh-Throughput Nucleotide SequencingHumansMitochondriaMutationSequence Analysis, DNADNA-Directed DNA PolymeraseDNA, MitochondrialDNA polymeraseheteroplasmymitochondrial DNA (mtDNA)next generation sequencing (NGS)variant callers

Identifiers

PMID33477827
PMCPMC7832847

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.